IDEAS home Printed from https://ideas.repec.org/a/gam/jworld/v3y2022i4p42-771d919910.html
   My bibliography  Save this article

Eco-Efficiency of Agriculture in the Amazon Biome: Robust Indices and Determinants

Author

Listed:
  • Carlos Rosano-Peña

    (Administration Department, Faculty of Administration, Accounting, Economics and Public Policy Management, Campus Darcy Ribeiro, University of Brasília (UnB), Brasília 70910-900, Brazil)

  • João Vitor Borges Silva

    (Administration Department, Faculty of Administration, Accounting, Economics and Public Policy Management, Campus Darcy Ribeiro, University of Brasília (UnB), Brasília 70910-900, Brazil)

  • André Luiz Marques Serrano

    (Administration Department, Faculty of Administration, Accounting, Economics and Public Policy Management, Campus Darcy Ribeiro, University of Brasília (UnB), Brasília 70910-900, Brazil)

  • José Eustáquio Ribeiro Vieira Filho

    (Institute for Applied Economic Research (IPEA), Brasília 70390-025, Brazil)

  • Herbert Kimura

    (Administration Department, Faculty of Administration, Accounting, Economics and Public Policy Management, Campus Darcy Ribeiro, University of Brasília (UnB), Brasília 70910-900, Brazil)

Abstract

This study analyzes the municipal agriculture eco-efficiency in the Amazon biome and the influence of exogenous factors. We use a two-stage data envelopment analysis (DEA) method with bootstrap. The results indicate that: (i) the density curve of the corrected eco-efficiency indices is statistically different from the deterministic score curves, suggesting the presence of bias in the latter; (ii) there is evidence of constant returns, demonstrating that small, medium and large municipalities can be equally eco-efficient; (iii) there are relevant eco-inefficient behaviors, showing that it is possible to increase the products (gross revenue and preserved area) and simultaneously reduce environmental damage (impact on biodiversity and greenhouse gas emission indices) with the same inputs, by replicating the best practices; and (iv) eco-efficiency scores are also substantially affected by exogenous factors. Based on the results, strategies can be defined by decision-makers to harmonize economic growth and environmental preservation; in addition, adaptive policies and actions can be adopted to optimize the sustainability of regional agriculture.

Suggested Citation

  • Carlos Rosano-Peña & João Vitor Borges Silva & André Luiz Marques Serrano & José Eustáquio Ribeiro Vieira Filho & Herbert Kimura, 2022. "Eco-Efficiency of Agriculture in the Amazon Biome: Robust Indices and Determinants," World, MDPI, vol. 3(4), pages 1-19, September.
    • Handle: RePEc:gam:jworld:v:3:y:2022:i:4:p:42-771:d:919910
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2673-4060/3/4/42/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2673-4060/3/4/42/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R. E. Caves & M. E. Porter, 1977. "From Entry Barriers to Mobility Barriers: Conjectural Decisions and Contrived Deterrence to New Competition," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 91(2), pages 241-261.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Bravo-Ureta, Boris E. & Pinheiro, António E., 1993. "Efficiency Analysis of Developing Country Agriculture: A Review of the Frontier Function Literature," Agricultural and Resource Economics Review, Cambridge University Press, vol. 22(1), pages 88-101, April.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Ondersteijn, C.J.M. & Giesen, G.W.J. & Huirne, R.B.M., 2006. "Perceived environmental uncertainty in Dutch dairy farming: The effect of external farm context on strategic choice," Agricultural Systems, Elsevier, vol. 88(2-3), pages 205-226, June.
    6. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    7. Mei Xue & Patrick T. Harker, 1999. "Overcoming the Inherent Dependency of DEA Efficiency Scores: A Bootstrap Approach," Center for Financial Institutions Working Papers 99-17, Wharton School Center for Financial Institutions, University of Pennsylvania.
    8. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    9. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    10. Roll, Y. & Golany, B. & Seroussy, D., 1989. "Measuring the efficiency of maintenance units in the Israeli Air Force," European Journal of Operational Research, Elsevier, vol. 43(2), pages 136-142, November.
    11. Maria Sousa & Borko Stošić, 2005. "Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers," Journal of Productivity Analysis, Springer, vol. 24(2), pages 157-181, October.
    12. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    13. Wilson, Paul W., 2008. "FEAR: A software package for frontier efficiency analysis with R," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 247-254, December.
    14. Shili Guo & Zhiyong Hu & Hanzhe Ma & Dingde Xu & Renwei He, 2022. "Spatial and Temporal Variations in the Ecological Efficiency and Ecosystem Service Value of Agricultural Land in China," Agriculture, MDPI, vol. 12(6), pages 1-23, June.
    15. Wilson, Paul W, 1993. "Detecting Outliers in Deterministic Nonparametric Frontier Models with Multiple Outputs," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 319-323, July.
    16. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    17. Alves, Eliseu Roberto de Andrade, 2004. "Retornos à escala e mercado competitivo: teoria e evidências empíricas," Revista de Economia e Agronegócio / Brazilian Review of Economics and Agribusiness, Federal University of Vicosa, Department of Agricultural Economics, vol. 2(3), pages 1-23.
    18. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    19. Timothy G. Taylor & H. Evan Drummond & Aloisio T. Gomes, 1986. "Agricultural Credit Programs and Production Efficiency: An Analysis of Traditional Farming in Southeastern Minas Gerais, Brazil," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(1), pages 110-119.
    20. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    21. Porter, Michael E, 1979. "The Structure within Industries and Companies' Performance," The Review of Economics and Statistics, MIT Press, vol. 61(2), pages 214-227, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    2. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    3. Massimo Finocchiaro Castro & Calogero Guccio & Ilde Rizzo, 2014. "An assessment of the waste effects of corruption on infrastructure provision," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 21(4), pages 813-843, August.
    4. AGRELL, Per J. & NIKNAZAR, Pooria, 2014. "Structural and behavioral robustness in applied best practice regulation," LIDAM Reprints CORE 2557, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Agrell, Per J. & Niknazar, Pooria, 2014. "Structural and behavioral robustness in applied best-practice regulation," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 89-103.
    6. Galina Besstremyannaya, 2013. "The impact of Japanese hospital financing reform on hospital efficiency: A difference-in-difference approach," The Japanese Economic Review, Japanese Economic Association, vol. 64(3), pages 337-362, September.
    7. Michael Zschille & Matthias Walter, 2012. "The performance of German water utilities: a (semi)-parametric analysis," Applied Economics, Taylor & Francis Journals, vol. 44(29), pages 3749-3764, October.
    8. Varabyova, Yauheniya & Schreyögg, Jonas, 2013. "International comparisons of the technical efficiency of the hospital sector: Panel data analysis of OECD countries using parametric and non-parametric approaches," Health Policy, Elsevier, vol. 112(1), pages 70-79.
    9. Calogero Guccio & Marco Ferdinando Martorana & Luisa Monaco, 2016. "Evaluating the impact of the Bologna Process on the efficiency convergence of Italian universities: a non-parametric frontier approach," Journal of Productivity Analysis, Springer, vol. 45(3), pages 275-298, June.
    10. Dana PANCUROVA & Stefan LYOCSA, 2013. "Determinants of Commercial Banks’ Efficiency: Evidence from 11 CEE Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(2), pages 152-179, May.
    11. Isabel Narbón-Perpiñá & Kristof De Witte, 2016. "Local governments’ efficiency: A systematic literature review – Part II," Working Papers 2016/21, Economics Department, Universitat Jaume I, Castellón (Spain).
    12. Marcel Clermont & Julia Schaefer, 2019. "Identification of Outliers in Data Envelopment Analysis," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 475-496, October.
    13. Quaranta, Anna Grazia & Raffoni, Anna & Visani, Franco, 2018. "A multidimensional approach to measuring bank branch efficiency," European Journal of Operational Research, Elsevier, vol. 266(2), pages 746-760.
    14. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    15. Bernardino Benito & José Solana & María-Rocío Moreno, 2014. "Explaining efficiency in municipal services providers," Journal of Productivity Analysis, Springer, vol. 42(3), pages 225-239, December.
    16. Iparraguirre, José Luis & Ma, Ruosi, 2015. "Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 33-46.
    17. Aggelopoulos, Eleftherios & Georgopoulos, Antonios, 2017. "Bank branch efficiency under environmental change: A bootstrap DEA on monthly profit and loss accounting statements of Greek retail branches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1170-1188.
    18. Olesen, Ole B. & Petersen, Niels Christian, 2016. "Stochastic Data Envelopment Analysis—A review," European Journal of Operational Research, Elsevier, vol. 251(1), pages 2-21.
    19. Thiago Victorino & Carlos Rosano Peña, 2023. "The Development of Efficiency Analysis in Transportation Systems: A Bibliometric and Systematic Review," Sustainability, MDPI, vol. 15(13), pages 1-32, June.
    20. Davtalab-Olyaie, Mostafa & Asgharian, Masoud & Nia, Vahid Partovi, 2019. "Stochastic ranking and dominance in DEA," International Journal of Production Economics, Elsevier, vol. 214(C), pages 125-138.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jworld:v:3:y:2022:i:4:p:42-771:d:919910. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.